The Landscape of Immunotherapy for Retroperitoneal Sarcoma
Bibliographic record
Abstract
Significant multidisciplinary scientific effort has been undertaken to understand the heterogeneous family of neoplasms that comprise soft tissue sarcomas. Within this family of neoplasms, outcomes for retroperitoneal sarcomas (RPS) are currently limited given a lack of effective therapies. In this review, we focus on immunotherapy and its relationship with the common RPS histologic subtypes. Although initial outcomes for RPS patients with immune checkpoint inhibition alone have been somewhat disappointing, subsequent analyses on histologies, the tumor microenvironment, sarcoma immune class, tumor infiltrating lymphocytes and genetic analysis for tumor mutational burden have yielded insight into the interplay between sarcomas and immunotherapy. Such approaches have all provided critical insight into the environment and characterization of these tumors, with targets for potential immunotherapy in future clinical trials. With this insight, molecularly tailored combination treatments for improving response rates and oncologic outcomes for RPS are promising.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".